|
|
| ====================================================================== |
| ARGUMENTS SUMMARY |
| ====================================================================== |
| model_name : openai/whisper-base |
| language : Pashto |
| intermediate_model_path : None |
| freeze_encoder_layers : 0 |
| freeze_encoder_ratio : 0.0 |
| freeze_feature_encoder : False |
| use_lora : True |
| lora_rank : 64 |
| lora_alpha : 128 |
| lora_dropout : 0.1 |
| sampling_rate : 16000 |
| num_proc : 1 |
| train_datasets : ['ihanif/pashto_augmented_speech'] |
| train_dataset_configs : ['default'] |
| train_dataset_splits : ['train'] |
| train_dataset_text_columns : ['sentence'] |
| eval_datasets : ['ihanif/pashto_augmented_speech'] |
| eval_dataset_configs : ['default'] |
| eval_dataset_splits : ['test'] |
| eval_dataset_text_columns : ['sentence'] |
| max_eval_samples : None |
| augment_speed : False |
| augment_pitch : False |
| augment_noise : False |
| augment_volume : False |
| augment_reverb : False |
| noise_snr : 15.0 |
| augment_probability : 0.7 |
| train_strategy : steps |
| learning_rate : 0.0001 |
| warmup_steps : 500 |
| warmup_ratio : 0.1 |
| train_batchsize : 32 |
| eval_batchsize : 16 |
| gradient_accumulation_steps : 2 |
| dataloader_num_workers : 0 |
| num_epochs : 10 |
| num_steps : 10000 |
| max_duration_in_seconds : 30.0 |
| min_duration_in_seconds : 0.5 |
| eval_strategy : steps |
| eval_steps : 500 |
| save_strategy : steps |
| save_steps : 500 |
| save_total_limit : 1 |
| logging_steps : 100 |
| compute_cer : True |
| eval_ortho_wer : True |
| gradient_checkpointing : False |
| fp16 : False |
| bf16 : True |
| weight_decay : 0.01 |
| output_dir : /workspace/experiments/exp_002_base_lora |
| overwrite_output_dir : False |
| resume_from_checkpoint : True |
| push_to_hub : True |
| use_auth_token : True |
| hub_model_id : None |
| report_to : ['tensorboard'] |
| push_augmented_dataset : False |
| augmented_dataset_id : None |
| augmented_dataset_private : False |
| augmented_dataset_include_eval: True |
| hub_token : None |
| early_stopping_patience : 5 |
| metric_for_best_model : wer |
| greater_is_better : False |
| load_best_model_at_end : True |
| ====================================================================== |
|
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| Setting up LoRA (rank=64, alpha=128)... |
| trainable params: 2,359,296 || all params: 74,953,216 || trainable%: 3.1477 |
| ✓ LoRA configured |
| Loading and preparing datasets... |
| Loading train dataset: ihanif/pashto_augmented_speech (config: default, split: train) |
| Loading eval dataset: ihanif/pashto_augmented_speech (config: default, split: test) |
| Train dataset size: 49906 |
| Eval dataset size: 2801 |
|
|
| ====================================================================== |
| PREPROCESSING DATASETS |
| ====================================================================== |
| Train samples: 49906 |
| Eval samples: 2801 |
| Workers: 1 |
| ====================================================================== |
|
|
| Testing preprocessing on first sample... |
| ✓ Preprocessing test passed |
|
|
| Processing 49906 training samples with 1 workers... |
| (This may take 10-30 minutes on first run. Progress updates every ~1000 samples.) |
|
|
|
|
| Processing 2801 eval samples... |
|
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Filtering eval dataset: 71%|███████▏ | 2000/2801 [04:18<01:14, 10.72 examples/s]
Filtering eval dataset: 100%|██████████| 2801/2801 [04:20<00:00, 10.78 examples/s]
Filtering eval dataset: 100%|██████████| 2801/2801 [04:20<00:00, 10.76 examples/s] |
| After filtering - Train: 49906, Eval: 2801 |
| ✓ Early stopping enabled (patience=5) |
|
|
| ====================================================================== |
| STARTING TRAINING |
| ====================================================================== |
| Model: openai/whisper-base |
| Language: Pashto |
| Train samples: 49906 |
| Eval samples: 2801 |
| LoRA: rank=64, alpha=128 |
| Early stopping: patience=5 |
| Output directory: /workspace/experiments/exp_002_base_lora |
| ====================================================================== |
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5%|▌ | 500/10000 [59:25<18:26:19, 6.99s/it]Using custom `forced_decoder_ids` from the (generation) config. This is deprecated in favor of the `task` and `language` flags/config options. |
| Transcription using a multilingual Whisper will default to language detection followed by transcription instead of translation to English. This might be a breaking change for your use case. If you want to instead always translate your audio to English, make sure to pass `language='en'`. See https://github.com/huggingface/transformers/pull/28687 for more details. |
| The attention mask is not set and cannot be inferred from input because pad token is same as eos token. As a consequence, you may observe unexpected behavior. Please pass your input's `attention_mask` to obtain reliable results. |
| A custom logits processor of type <class 'transformers.generation.logits_process.SuppressTokensLogitsProcessor'> has been passed to `.generate()`, but it was also created in `.generate()`, given its parameterization. The custom <class 'transformers.generation.logits_process.SuppressTokensLogitsProcessor'> will take precedence. Please check the docstring of <class 'transformers.generation.logits_process.SuppressTokensLogitsProcessor'> to see related `.generate()` flags. |
| A custom logits processor of type <class 'transformers.generation.logits_process.SuppressTokensAtBeginLogitsProcessor'> has been passed to `.generate()`, but it was also created in `.generate()`, given its parameterization. The custom <class 'transformers.generation.logits_process.SuppressTokensAtBeginLogitsProcessor'> will take precedence. Please check the docstring of <class 'transformers.generation.logits_process.SuppressTokensAtBeginLogitsProcessor'> to see related `.generate()` flags. |
| {'loss': '10.19', 'grad_norm': '7.154', 'learning_rate': '9.9e-06', 'epoch': '0.1282'} |
| {'loss': '6.782', 'grad_norm': '4.674', 'learning_rate': '1.99e-05', 'epoch': '0.2564'} |
| {'loss': '5.307', 'grad_norm': '5.673', 'learning_rate': '2.99e-05', 'epoch': '0.3846'} |
| {'loss': '4.85', 'grad_norm': '6.753', 'learning_rate': '3.99e-05', 'epoch': '0.5128'} |
| {'loss': '4.639', 'grad_norm': '8.368', 'learning_rate': '4.99e-05', 'epoch': '0.641'} |
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[A
5%|▌ | 500/10000 [1:06:14<18:26:19, 6.99s/it] |
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[A
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10%|█ | 1000/10000 [2:04:16<17:17:23, 6.92s/it]{'eval_loss': '1.308', 'eval_wer': '87.45', 'eval_wer_ortho': '88.95', 'eval_cer': '28.66', 'eval_runtime': '409', 'eval_samples_per_second': '6.849', 'eval_steps_per_second': '0.43', 'epoch': '0.641'} |
| {'loss': '4.384', 'grad_norm': '8.012', 'learning_rate': '5.99e-05', 'epoch': '0.7692'} |
| {'loss': '4.219', 'grad_norm': '7.629', 'learning_rate': '6.99e-05', 'epoch': '0.8974'} |
| {'loss': '4.068', 'grad_norm': '8.435', 'learning_rate': '7.99e-05', 'epoch': '1.026'} |
| {'loss': '3.928', 'grad_norm': '6.346', 'learning_rate': '8.99e-05', 'epoch': '1.154'} |
| {'loss': '3.805', 'grad_norm': '6.379', 'learning_rate': '9.99e-05', 'epoch': '1.282'} |
|
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[A
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[A
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15%|█▌ | 1500/10000 [3:09:02<16:30:31, 6.99s/it]{'eval_loss': '0.9918', 'eval_wer': '76.15', 'eval_wer_ortho': '78.72', 'eval_cer': '24.68', 'eval_runtime': '419.8', 'eval_samples_per_second': '6.673', 'eval_steps_per_second': '0.419', 'epoch': '1.282'} |
| {'loss': '3.705', 'grad_norm': '5.792', 'learning_rate': '9.89e-05', 'epoch': '1.41'} |
| {'loss': '3.604', 'grad_norm': '5.786', 'learning_rate': '9.779e-05', 'epoch': '1.538'} |
| {'loss': '3.485', 'grad_norm': '6.041', 'learning_rate': '9.668e-05', 'epoch': '1.667'} |
| {'loss': '3.46', 'grad_norm': '5.259', 'learning_rate': '9.557e-05', 'epoch': '1.795'} |
| {'loss': '3.368', 'grad_norm': '4.825', 'learning_rate': '9.446e-05', 'epoch': '1.923'} |
|
|
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0%| | 0/176 [00:00<?, ?it/s][A |
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1%| | 2/176 [00:02<03:16, 1.13s/it][A |
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[A
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[A
15%|█▌ | 1501/10000 [3:16:06<311:16:00, 131.85s/it] |
